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An important consideration in epileptic seizure prediction is proving the existence of a pre-seizure state that can be detected using various signal processing algorithms. In the analyses of intracranial electroencephalographic (EEG)recordings of four epilepsy patients, the short-term changes in the measures of complexity and synchrony were detected before the majority of seizure events across the sample patient population. A decrease in complexity and increase in phase synchrony appeared several minutes before seizure onset and the changes were more pronounced in the focal region than in the remote region. This result was also validated statistically using a surrogate data method.
An important consideration in epileptic seizure prediction is proving the existence of a pre-seizure state that can be detected using various signal processing algorithms. In the analyzes of intracranial electroencephalographic (EEG) recordings of four epilepsy patients, the short-term changes in the measures of complexity and synchrony were detected before the majority of seizure events across the sample patient population. A decrease in complexity and increase in phase synchrony result was also validated statistically using a surrogate data method.